Compute the S fit statistic for a set of items
The base class for 1 dimensional response probability functions.
Computes local dependence indices for all pairs of items
Liking for Science dataset
Compress a data frame into unique rows and frequencies
Map an item model, item parameters, and person trait score into a
information vector
Compute the S fit statistic for 1 item
Retrieve a description of the given parameter
Length of the item model vector
Write a flexMIRT PRM file
Knox Cube Test dataset
Generates item parameters
Rescale item parameters
Transform from [0,1] to the reals
Produce an item outcome by observed sum-score table
Item parameter derivatives
Find the point where an item provides mean maximum information
Compute the ordinal gamma association statistic
Order a data.frame by missingness and all columns
Read a flexMIRT PRM file
The base class for multi-dimensional response probability functions.
The unidimensional graded response item model.
Map an item model, item parameters, and person trait score into a
probability vector
The nominal response item model (both unidimensional and
multidimensional models have the same parameterization).
Find the point where an item provides mean maximum information
The multiple-choice response item model (both unidimensional and
multidimensional models have the same parameterization).
The multidimensional graded response item model.
Create a nominal response model
Expand summary table of patterns and frequencies
Create a dichotomous response model
Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
Randomly sample response patterns given a list of items
Compute EAP scores
Calculate residuals
Conduct the sum-score EAP distribution test
Convert an OpenMx MxModel object into an IFA group
Item derivatives with respect to the location in the latent space
The base class for 1 dimensional graded response probability functions.
rpf - Response Probability Functions
Map an item model, item parameters, and person trait score into a
probability vector
Create a similar item specification with the given number of factors
Convert an rpf item model name to an ID
The base class for multi-dimensional graded response probability
functions.
Multinomial fit test
Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
The base class for response probability functions.
Calculate standardized residuals
Compute the sum-score EAP table
Monte-Carlo test for cross-tabulation tables
Compute the P value that the observed and expected tables come from the same distribution
The ogive constant
Calculate item and person Rasch fit statistics
Omit items with the most missing data
Calculate cell central moments
Create a multiple-choice response model
Tabulate data.frame rows
Compute the observed sum-score
Create a graded response model
Length of the item parameter vector